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Abstract

The invention discloses an establishing method for a fault tree. The establishing method comprises the following steps of: resolving fault reasons layer by layer to obtain the reason of each layer; determining a severity weight coefficient of each layer of reason; determining a frequency degree weight coefficient of each layer of reason; establishing the fault tree, wherein fault phenomena and various reasons form various components of the fault tree; arraying the various components according to the resolving relationship; arraying various reasons resolved from the same component according to the severity weight coefficient from small or large or from large to small; expressing the logical relation between each reason and next layer of reason resolved from the reason; and marking the frequency degree weight coefficient for each reason. According to the establishing method for the fault tress, which is disclosed by the invention, the severity and the weight coefficient of each fault phenomenon can be embodied while the mutual relation among various reasons causing the fault phenomena is embodied; and a complex mathematical model is not required. According to the establishing method, the fault tree can be quickly established for the fault phenomena according to the specific flow design.

Description

Translated from Chinese

ー种故障树的建立方法ー methods in establishing fault tree

技术领域 FIELD

[0001] 本发明属于故障诊断领域，尤其涉及ー种故障树的建立方法。 [0001] The present invention is in the field of fault diagnosis, in particular, relates to a method for establishing ー fault tree species.

背景技术 Background technique

[0002] 故障树分析是用于大型复杂系统可靠性、安全性分析和风险评价的ー种重要方法，它是通过对造成产品故障的硬件、软件、环境、人为因素进行分析，建立故障树模型，从而确定产品故障的各种可能原因。 [0002] Fault Tree Analysis is a large and complex system reliability, methods ー kinds of important safety analysis and risk assessment, it is through the analysis of product failure caused by hardware, software, environment, human factors, to establish the fault tree model to determine the possible causes of product failure.传统的故障树建立方法存在如下不足：1)在故障树建立的过程中未考虑故障原因严重程度和频繁程度；2)即使考虑了故障原因严重程度和频繁程度，但计算过程需要数学模型，在工程上难于实现。 There is a lack of traditional fault tree established: 1) In the process of fault tree established is not considered cause of the failure severity and how often; 2) even taking into account the cause of the failure severity and how often, but the calculation process requires a mathematical model, difficult to implement the project.

发明内容 SUMMARY

[0003] 本发明的目的是针对传统的故障树建立方法存在的不足，提供一种新的故障树的建立方法，该建立方法不但能够反映故障现象与故障原因之间的相互关系，而且能够快捷地得出故障原因的严重程度和频繁程度权重系数，具有良好的工程实现性。 [0003] The present invention is directed to traditional fault tree established shortcomings method, providing the establishment of a new method of fault tree, the method of establishing not only reflect the relationship between the Failure and cause of the malfunction, and can quickly to come to the cause of the severity and frequency of the degree of weighting coefficients, good engineering realizability.

[0004] 本发明采用的技术方案为：ー种故障树的建立方法，包括如下步骤： [0004] aspect of the present invention is used is: The method of establishing ー fault tree species, comprising the steps of:

[0005] 步骤1，故障分析単元根据输入的故障现象从知识库中获得引起所述故障现象的各直接原因，并将各直接原因设定为第一层；故障分析単元通过Ru代表与所述故障现象有关的各原因，i代表原因所在的层数，j代表原因Ru在第i层的序号，对应第i层的j的取值为I至Ni的所有自然数，其中，Ni为第i层的原因的数量，i=l的各原因为所述直接原因； [0005] Step 1, according to the failure analysis obtained radiolabeling membered Symptom knowledge base inputted from each of the direct causes of the phenomenon of failure, and sets each of the direct cause of the first layer; fault analysis by radiolabeling element representative of the Ru each of the cause of the failure phenomenon, i represents the number of layers of the reason, j represents the number reason Ru layer i, j corresponding to the i-th layer to the value of all the natural numbers Ni I, where, Ni is the i-th layer number of reasons, the reasons for each i = l for the direct cause;

[0008] 步骤4，故障分析単元通过查询知识库判断原因Ru是否存在可分解的下ー层原因，如存在则执行步骤5，如不存在则执行步骤6 ； [0008] Step 4, failure analysis radiolabeling by querying the knowledge base to determine the cause membered Ru layer ー whether the reason for the presence of a decomposable, such as the presence of the step 5, step 6 is performed if not present;

[0009] 步骤5，故障分析単元从知识库中读出由原因Ru分解出的原因，并将分解出的原因列至第i+1层，之后执行步骤6 ； [0009] Step 5, the fault reason analysis radiolabeling membered read by the reason Ru exploded from the knowledge base, and the reason the decomposition of the first column to the layer i + 1, after performing step 6;

[0012] 步骤8，故障分析単元根据查询结果判断第i层各原因是否均无法分解，如是则执行步骤11，如否则执行步骤9; [0012] Step 8, radiolabeling fault analysis element is determined whether the i layer of each reason are not decomposed, in the case a step 11 is performed, otherwise step 9 as according to the query result;

[0015] 步骤11，严重程度权重系数矩阵建立单元从故障分析单元读取各层原因，计算最大层数m，并执行i=l，之后执行步骤12 ； [0015] Step 11, the severity of the weight coefficient matrix creation unit reads from the failure analysis unit layers reasons, calculating the maximum number of layers m, and executes i = l, then step 12 is performed;

[0016] 步骤12，确定第i层原因的严重程度权重系数，之后执行步骤13 ;确定严重程度权重系数的方法如下： [0016] Step 12, determine the severity of the weight coefficient of the i-th layer reason, after performing step 13; The method of determining the severity level of the weight coefficients are as follows:

[0017] 严重程度权重系数矩阵建立单元对第i层原因按第i顺序排列，并针对第i层原因建立Ni X Ni的严重程度权重系数矩阵Ui ;严重程度权重系数矩阵Ui的元素ui (x，y)的数值为第X个原因与第y个原因相比得到的标度值，其中，ui (x，y)表示严重程度权重系数矩阵Ui的第X行第y列元素；x、y的取值均为从I至Ni的所有自然数；严重程度权重系数矩阵建立単元将严重程度权重系数矩阵Ui的所有元素的数值均发送至严重程度权重系数计算单元，严重程度权重系数计算单元计算严重程度权重系数矩阵ui的最大特征值所对应的特征向量，并将得到的特征向量归ー化，归ー化后向量中的各元素值按第i顺序对应第i层各原因的严重程度权重系数； [0017] severity of the weight coefficient matrix creating unit to the first i-layer reasons arranged in the i-th order, and to establish the severity of the weight coefficient matrix Ui Ni X Ni for the i-th layer reasons; the severity of the weight coefficient matrix Ui elements ui (x , the value y) is the X-th Causes of y reason in comparison scale values, where, ui (x, y) represents the severity of the weight coefficient matrix row X Ui y-th column element; X, y values ​​are I to all the natural numbers Ni from; the severity of the weight coefficient matrix established radiolabeling membered the severity of the weight coefficient matrix values ​​of all elements Ui are transmitted to the severity of the weight coefficient calculation unit, the severity of the weighting coefficient calculating unit calculates serious the degree of weight coefficient matrix ui largest eigenvalue corresponding to the eigenvector and the resulting feature vector normalization ー, post normalized ー of each element values ​​in the vector according to the i-th order corresponding to the i layer of each reason severity weighting coefficient ;

[0018] 严重程度权重系数矩阵建立単元确定严重程度权重系数矩阵Ui的各元素的数值的方法为：使第i层的每个原因均与第i层的所有原因进行两两比较，第X个原因与第y个原因同样严重则标度值为1，第X个原因比第y个原因稍微严重则标度值为3，第X个原因比第y个原因明显严重则标度值为5，第X个原因比第y个原因强烈严重则标度值为7，第X个原因比第y个原因极端严重则标度值为9 ;x、y取值互置的元素ui(x,y)的数值互为倒数，x、y取值相同的元素ui(x，y)的数值为I ;所述严重程度权重系数矩阵建立単元从知识库获得对第i层的所有原因进行针对严重程度进行两两比较的标度值； [0018] severity of the weight coefficient matrix method for establishing radiolabeling element determining the severity of the weight coefficient matrix the value of each element Ui is as follows: each reason of the first i-layer are pairwise comparison with all-cause i-th layer, the X-th reasons and equally serious reason of the y scale value of 1, the second reason is slightly worse than X y reason of the scale value is 3, the X-th reason for the apparent reason severe than the y-value scale 5 the first reason strong X y reason of serious than the scale value is 7, the first X reason extremely serious than the first y reason the scale is 9; x, y values ​​mutually opposite elements ui (x, value of y) is reciprocal, x, y values ​​of the same element value of ui (x, y) is i; the severity of the weight coefficient matrix is ​​obtained from the metadata repository radiolabeling established for all the reasons for the i-th layer is seriously degree scale values ​​for pairwise comparison;

[0020] 步骤14，严重程度权重系数矩阵建立単元判断i是否小于等于m，如是则执行步骤12，如否则执行步骤15; [0020] Step 14, the severity of the weight coefficient matrix is ​​determined to establish radiolabeling element i is less than equal to m, the case of the step 12, as otherwise step 15;

[0021] 步骤15，频繁程度权重系数矩阵建立单元从故障分析单元读取各层原因，计算最大层数m，并执行i=l，之后执行步骤16 ； [0021] Step 15, how often establishing unit weight coefficient matrix the reason for the failure analysis unit reads the respective layers, calculating the maximum number of layers m, and executes i = l, after performing step 16;

[0022] 步骤16，确定第i层原因的频繁程度权重系数，之后执行步骤17 ;确定频繁程度权重系数的方法如下： [0022] Step 16, the weight coefficient is determined how often the cause of the i-layer, after performing step 17; how often the method of determining weight coefficients are as follows:

[0023] 频繁程度权重系数矩阵建立单元对第i层原因按第i顺序排列，并针对第i层原因建立Ni X Ni的频繁程度权重系数矩阵fi ;频繁程度权重系数矩阵fi的元素fi(x，y)的数值为第X个原因与第y个原因相比得到的标度值，其中，fi(x，y)表示频繁程度权重系数矩阵fi的第X行第y列元素；x、y的取值均为从I至Ni的所有自然数；频繁程度权重系数矩阵建立単元将频繁程度权重系数矩阵fi的所有元素的数值均发送至频繁程度权重系数计算单元，频繁程度权重系数计算单元计算频繁程度权重系数矩阵fi的最大特征值所对应的特征向量，并将得到的特征向量归ー化，归ー化后向量中的各元素值按第i顺序对应第i层各原因的频繁程度权重系数； [0023] how often the weight coefficient matrix creating unit according to the i-th order of the i-th layer reasons, and to establish how often the weight coefficient matrix fi Ni X Ni for the i-th layer causes; how often the weight coefficient matrix elements fi fi (x- , the value y) is the X-th Causes of y reason comparison obtained scaling value, wherein, fi (X, y) indicates how often the weight coefficient matrix row X fi y-th column element; X, y values ​​are from whole natural number from I to Ni; and how often the weight coefficient matrix established radiolabeling membered frequently degree weighting coefficient matrix values ​​of all elements fi are sent to the weighting coefficient how often the weight calculation unit how often the weight coefficient calculation unit calculates frequently the degree of weight coefficient matrix fi largest eigenvalue corresponding to the eigenvector and the resulting feature vector normalization ー, post normalized ー of each element values ​​in the vector according to the i-th order corresponding i-th layer how frequently weighting coefficients cause ;

[0024] 频繁程度权重系数矩阵建立单元确定频繁程度权重系数矩阵fi的各元素的数值的方法为：使第i层的每个原因均与第i层的所有原因进行两两比较，第X个原因与第y个原因同样频繁则标度值为1，第X个原因比第y个原因稍微频繁则标度值为2，第X个原因比第y个原因明显频繁则标度值为4，第X个原因比第y个原因强烈频繁则标度值为6，第X个原因比第y个原因极端频繁则标度值为8 ;x、y取值互置的两个元素fi(x，y)的数值互为倒数，x、y取值相同的元素fi(x，y)的数值为I ;所述频繁程度权重系数矩阵建立单元从知识库获得对第i层的所有原因进行针对频繁程度进行两两比较的标度值； [0024] how often the weighting coefficient matrix methods unit determines how often the weight coefficient matrix the value of each element fi is established as: that the i-th layer for each reason are pairwise comparison with all-cause i-th layer, the X-th Causes of y reason as frequently as the scale value of 1, X reason of slightly more frequently than the first y reason the scale value is 2, the X-th reason for the apparent reason frequently than the y value of the scale 4 , the X reason strong reason frequently than the y-scale value of 6, the first X terminal reason frequent reason than the y value of the scale 8; x, y values ​​of two mutually opposite elements fi ( values ​​of x, y) of the reciprocal, x, y values ​​of the same element values ​​Fi (x, y) is i; how often the weight coefficient matrix is ​​obtained for all the reasons establishing unit i-th layer from the knowledge base be scaled value for pairwise comparison of how often;

[0025] 步骤17，频繁程度权重系数矩阵建立单元执行i=i+l，之后执行步骤18 ；[0026] 步骤18，频繁程度权重系数矩阵建立単元判断i是否小于等于m，如是则执行步骤16，如否则执行步骤19; [0025] Step 17, how often the weight coefficient matrix creating unit performs i = i + l, after performing step 18; [0026] Step 18, how often weight coefficient matrix established radiolabeling element determines whether i is less than equal to m, if so perform step 16 as otherwise step 19;

[0027] 步骤19，故障树建立单元从故障分析单元读取所述故障现象，从严重程度权重系数计算单元读取各原因的严重程度权重系数，从频繁程度权重系数计算单元读取各原因的频繁程度权重系数，并建立故障树，故障现象和各原因构成故障树的各组分，故障树的树根为故障现象，各组分按分解关系排列，由同一组分分解出的各原因按照严重程度权重系数从小到大或从大到小进行排列，并表示出各组分和由其分解出的下ー层原因间的逻辑关系，及为各原因标注自身的频繁程度权重系数，所述逻辑关系由故障树建立単元从所述知识库中获取。 [0027] Step 19, the fault tree creation unit fault analysis unit reads from the symptoms, the severity of the weight coefficient calculated from the weight unit reads the severity of the weight of each weighting coefficients reason, calculated from the weight coefficient of each unit to read how often cause weight how often each component weighting coefficient, and establish the fault tree, and each Symptom constitute a cause of the fault tree, the tree is a root failure symptoms, the components are arranged in an exploded relationship, each of the reason the decomposition of the same component in accordance with the the severity of the weighting factor for ascending or descending order, and shows the logical relationship between the various components and by reason of the lower layer is decomposed ー, marked and how often their weight coefficients for the reason, the created by the fault tree logic element radiolabeling obtained from the knowledge base.[0028] 其中，所述建立方法为针对电子信息系统的故障检测的建立方法。 [0028] wherein, the establishing method for establishing a failure detection method for an electronic information system.

[0029] 本发明的有益效果为：本发明的故障树的建立方法在体现引发故障现象的各原因间的相互关系的同时也能够体现各故障现象的严重程度和权重系数，并且无需建立复杂的数学模型，本发明通过特定的流程设计可以针对输入的故障现象快捷地建立故障树。 [0029] the beneficial effects of the present invention are: To establish a method of fault tree of the present invention, while the relationship between the various reasons reflect the risk of failure phenomenon can also be reflected in the severity and weight of each fault phenomenon of weight coefficients, and without having to build complex mathematical model, the present invention can establish the fault tree for failure phenomenon quickly entered through a specific process design.

附图说明 BRIEF DESCRIPTION

[0030] 图I为本发明的故障树的建立方法的流程示意图的一部分； Process [0030] The method for establishing a fault tree of Figure I is a schematic view of a part of the present invention;

[0031] 图2为本发明的故障树的建立方法的流程示意图的与图I承接的另一部分； [0031] FIG 2 flow for establishing the method of the present invention, the fault tree is a schematic diagram of another portion of FIG. I undertake;

[0032] 图3为本发明的实施例根据图I和2所述建立方法得到的故障树的ー种结构。 Example ー species fault tree structure of FIGS. I and 2 of the method for establishing obtained embodiment [0032] FIG. 3 of the present invention.

具体实施方式 detailed description

[0033] 本实施例将如图I和2所示的故障树的建立方法应用于电子信息系统，当电子信息系统出现“电脑屏幕无显示”的故障现象时，对应该故障现象的故障树的建立过程如下： [0033] The method of the present embodiment will be established as shown in Example I and the fault tree of Figure 2 applied to an electronic information system, when the electronic information system in the "computer screen no display" failure phenomenon, the phenomenon of the failure should be fault tree build process is as follows:

[0034] 步骤1，故障分析単元根据输入的故障现象从知识库中获得引起该故障现象的各直接原因，其中，知识库中对应“电脑屏幕无显示”的直接原因为主机损坏、屏幕损坏和接线损坏，故障分析単元将获得的各直接原因表示为主机损坏Rn、屏幕损坏R12和接线损坏R13;在此，故障分析単元通过Ru代表与该故障现象有关的各原因，i代表原因所在的层数，j代表原因Ru在第i层的序号（即故障分析单元将对各层原因进行排序)，对应第i层的j的取值为I至Ni的所有自然数，其中，Ni为第i层的原因的数量，i=l的各原因为上述直接原因； Direct cause [0034] Step 1, each of the failure analysis obtained radiolabeling membered direct causes of the fault phenomenon to prevent the phenomenon from the knowledge base input, wherein the knowledge base corresponding to "no display computer screen" for host damage, damage to the screen, and wiring damage, failure analysis of each direct cause of radiolabeling element obtained was expressed as a host damage Rn, damage to the screen R12 and damage to the wiring R13; here, failure analysis of each reason radiolabeling membered by representatives Ru relating to the fault, layer i represents reason of number, j represents the number reason Ru i-th layer (i.e., fault reason analysis unit layers will be sorted), j corresponding to the i-th layer I to the value of all the natural numbers Ni, where, Ni is the i-th layer number of reasons, the reasons for each i = l is the direct cause of the above;

[0037] 步骤4，故障分析単元通过查询知识库判断原因Ru是否存在可分解的下ー层原因，如存在则执行步骤5，如不存在则执行步骤6 ； [0037] Step 4, failure analysis radiolabeling by querying the knowledge base to determine the cause membered Ru layer ー whether the reason for the presence of a decomposable, such as the presence of the step 5, step 6 is performed if not present;

[0038] 步骤5，故障分析単元从知识库中读出由原因Ru分解出的原因，并将分解出的原因列至第i+1层，之后执行步骤6 ； [0038] Step 5, the fault reason analysis radiolabeling membered read by the reason Ru exploded from the knowledge base, and the reason the decomposition of the first column to the layer i + 1, after performing step 6;

[0041] 步骤8，故障分析単元根据查询结果判断第i层各原因是否均无法分解，如是则执行步骤11，如否则执行步骤9;[0042] 步骤9，故障分析単元计算第i层分解出的第i+1层的原因的数量Ni+1，之后执行步骤10 ； [0041] Step 8, the failure analysis radiolabeling element according to the query result of the determination of the i layer of each reason whether all not break down, and if so is executed in step 11, as otherwise step 9; [0042] Step 9, fault analysis radiolabeling Element i-th layer decomposition the reason the number of the i + 1 layer Ni + 1, after execution of the step 10;

[0044] 在本实施例中，通过以上步骤2至步骤10，故障分析単元得到屏幕损坏R12和接线损坏R13不能够再分解，而主机损坏R11可以再分解为电源损坏R21、通信板卡损坏R22和主板损坏R23这三个原因，且电源损坏R21、通信板卡损坏R22和主板损坏R23这三个原因均不能再向下分解的分析结果； [0044] In the present embodiment, by the above step 2 to step 10, fault analysis radiolabeling membered give damage to the screen R12 and damage to the wiring R13 can no longer break down, and the host damage R11 may be further decomposed into power damage R21, communications boards damage R22 R23 and board damage these three reasons, and the power supply is damaged R21, R22 and communications boards damage R23 board damage these three reasons not longer downwardly decomposition analysis result;

[0045] 步骤11，严重程度权重系数矩阵建立单元从故障分析单元读取各层原因，计算最大层数m=2，并执行i=l，之后按照步骤12至14执行以下流程： [0045] Step 11, the severity of establishing unit weight coefficient matrix read from the fault reason analysis unit layers, calculating the maximum number of layers m = 2, and executes i = l, then follow the steps 12 to 14, the following processes:

[0046] (I)确定第一层原因的严重程度权重系数：严重程度权重系数矩阵建立单元对第ー层原因按第一顺序排列(本实施例中该第一顺序采用故障分析单元对第一层的排列顺序)，并针对第一层原因建立3X3的严重程度权重系数矩阵Ul ;严重程度权重系数矩阵Ul 的元素ul(x，y)的数值为第X个原因与第y个原因相比得到的标度值，其中，ul (x，y)表示严重程度权重系数矩阵Ul的第X行第y列元素；x、y的取值均为1、2和3 ;严重程度权重系数矩阵建立单元从知识库中查询到如下结果：主机损坏R11与屏幕损坏R12相比，标度值为7 ;主机损坏R11与接线损坏R13相比，标度值为9 ;屏幕损坏R12与接线损坏R13相比，标度值为5。 [0046] (I) a first layer of determining the severity of the reasons weight coefficients: the weight coefficient matrix severity of Reason ー establishing unit layers are arranged in a first order (in the present embodiment the failure analysis unit uses a first sequence of first the order layer), and to establish the severity of the weight coefficient matrix Ul 3X3 for the first layer causes; numerical severity weighting coefficient matrix Ul element ul (x, y) of the X-th compared with that of y reason the resulting scale value, wherein, UL (x, y) represents the X row severity weighting coefficient matrix column element Ul of y; values ​​x, y are 1, 2 and 3; the severity of established weight coefficient matrix query from the knowledge base unit to the following results: the host damage R11 R12 and damage to the screen as compared to the scale value of 7; host damage and damage to the wiring R13 compared to R11, the scale value of 9; damage to the screen and damage to the wiring R12 R13 phase ratio scale value of 5.

[0051] 严重程度权重系数矩阵建立単元将严重程度权重系数矩阵Ul的所有元素的数值均发送至严重程度权重系数计算单元，严重程度权重系数计算单元计算严重程度权重系数矩阵ul的最大特征值所对应的特征向量，并将得到的特征向量归ー化，归ー化得到的特征向量为[77. 2%, 17. 3%, 5. 5%]，归ー化后向量中的各元素值按第一顺序对应第一层各原因的严重程度权重系数，即主机损坏Rn、屏幕损坏R12和接线损坏R13的严重程度权重系数分别为77. 2%、17. 3% 和5. 5%o [0051] The severity of the weight coefficient matrix established radiolabeling element the value of all elements in the severity of the weight coefficient matrix Ul are transmitted to severe weight coefficient degree of weight calculating unit, the severity of the weighting coefficient calculating unit calculates the severity of the weight coefficient matrix ul maximum eigenvalue corresponding eigenvectors, and the resulting normalized eigenvectors ー, feature vector normalization is obtained ー of [77.2%, 17.3%, 5.5%], the value of each element in the vector of normalized ーa first layer of a first order corresponding to each of the reasons for the severity of the weighting factor, i.e., the host damage Rn, damage to the screen and damage to the wiring R13 R12 severity weighting coefficient 77.2%, 17.3% respectively, and 5. 5% o

[0052] (2)确定第二层原因的严重程度权重系数：严重程度权重系数矩阵建立单元对第ニ层原因按第二顺序排列(本实施例中该第二顺序采用故障分析单元对第二层的排列顺序)，并针对第二层原因建立3X3的严重程度权重系数矩阵u2 ;严重程度权重系数矩阵u2的元素u2(x，y)的数值为第X个原因与第y个原因相比得到的标度值，其中，u2(x，y)表示严重程度权重系数矩阵u2的第X行第y列元素；x、y的取值均为1、2和3 ;严重程度权重系数矩阵建立单元从知识库中查询到如下结果：主板损坏R23与通信板卡损坏R22相比，标度值为5 ;主板损坏R23与电源损坏R21相比，标度值为9 ;通信板卡损坏R22与电源损坏R21相比，标度值为7。 [0052] (2) determine the severity of the weight coefficient of the second layer causes: the severity of the weight coefficient matrix of the reasons for establishing unit according to a second order Ni layer (the second sequence of the present embodiment uses the failure analysis unit in the second embodiment the order layer), and to establish the severity of the right 3X3 for the second layer reasons weight coefficient matrix u2; weight coefficient matrix the elements and u2 u2 (X, y) values ​​severity right of the X-th compared with that of y reason the resulting scale value, wherein, u2 (x, y) represents the severity of the weight coefficient matrix row X u2 y-th column element; values ​​x, y are 1, 2 and 3; the severity of established weight coefficient matrix query from the knowledge base unit to the following result: a communication board damage R23 and R22 board damage compared to 5 scale value; R23 compared with the power board damage damage R21, scale is 9; R22 and a communication board damage R21 damaged power compared to the scale value of 7.

[0058] 步骤15，频繁程度权重系数矩阵建立单元从故障分析单元读取各层原因，计算最大层数m=2，并执行i=l，之后按照步骤16至18执行以下流程： [0058] Step 15, how often establishing unit weight coefficient matrix read from the fault reason analysis unit layers, calculating the maximum number of layers m = 2, and executes i = l, the following scheme after performing steps 16 to 18:

[0059] (I)确定第一层原因的频繁程度权重系数：频繁程度权重系数矩阵建立单元对第ー层原因按第一顺序排列(本实施例中该第一顺序采用故障分析单元对第一层的排列顺序)，并针对第一层原因建立3X3的频繁程度权重系数矩阵n ;频繁程度权重系数矩阵fl的元素fl(X，y)的数值为第X个原因与第y个原因相比得到的标度值，其中，fl(x，y)表示频繁程度权重系数矩阵fl的第X行第y列元素；x、y的取值均为1、2和3 ;频繁程度权重系数矩阵建立单元从知识库中查询到如下结果：屏幕损坏R12与主机损坏R11相比，标度值为2 ;接线损坏R13与主机损坏R11相比，标度值为6 ;接线损坏R13与屏幕损坏R12相比，标度值为4。 [0059] (I) a first layer of determining how frequently cause weight coefficients: the weight coefficient matrix how frequently the cause of establishing unit ー layers are arranged in a first order (first order in the present embodiment the failure analysis unit employed in the first embodiment the order layer), and to establish how often the weight coefficient matrix n 3X3 for the first layer causes; values ​​how often the weight coefficient matrix fl element fl (X, y) is the X-th compared with that of y reason the resulting scale value, wherein, fl (x, y) represents the X row weight coefficient matrix the degree of frequency of fl y column element; values ​​x, y are 1, 2 and 3; how often the weight coefficient matrix is ​​established query from the knowledge base unit to the following results: the host screen damage R12 R11 damage compared to the scale value of 2; damage to the wiring R13 R11 damage compared with the host, the scale value of 6; damage to the screen and damage to the wiring R13 R12 phase ratio scale value of 4.

[0060] 频繁程度权重系数矩阵建立单元获得的频繁程度权重系数矩阵n的各元素的数值为： [0060] The weight coefficient matrix how often to establish how often the unit weight value obtained by weighting coefficient of each element of the matrix n:

[0064] 频繁程度权重系数矩阵建立単元将频繁程度权重系数矩阵fl的所有元素的数值均发送至频繁程度权重系数计算单元，频繁程度权重系数计算单元计算频繁程度权重系数矩阵fl的最大特征值所对应的特征向量，并将得到的特征向量归ー化，归ー化得到的特征向量为[10. 6%, 19. 3%, 70. 1%],归ー化后向量中的各兀素值按第一顺序对应第一层各原因的频繁程度权重系数，即主机损坏Rn、屏幕损坏R12和接线损坏R13的频繁程度权重系数分别为10. 6%、19. 3% 和70. 1%。 [0064] how often the weight coefficient matrix established radiolabeling element the value of all the elements on how frequently weight coefficient matrix fl are sent to the weighting coefficient how often the weight calculation unit how often the weight coefficient calculation unit calculates how often the weight coefficient matrix fl maximum eigenvalue corresponding eigenvectors, and the resulting normalized eigenvectors ー, feature vector normalization is obtained ー of [10.6%, 19.3%, 70.1%], the normalized vector of each Wu Su ーvalues ​​in a first order corresponding to how often the cause of the weight of each weighting coefficient of the first layer, i.e., the host damage Rn, damage to the screen and damage to the wiring R13 R12 how frequently weight coefficients were 10.6%, 19.3% and 70.1% .

[0065] (2)确定第二层原因的频繁程度权重系数：频繁程度权重系数矩阵建立单元对第ニ层原因按第二顺序排列(本实施例中该第二顺序采用故障分析单元对第二层的排列顺序)，并针对第二层原因建立3X3的频繁程度权重系数矩阵f2 ;频繁程度权重系数矩阵f2的元素f2(x，y)的数值为第X个原因与第y个原因相比得到的标度值，其中，f2(x，y)表示频繁程度权重系数矩阵f2的第X行第y列元素；x、y的取值均为1、2和3 ;频繁程度权重系数矩阵建立单元从知识库中查询到如下结果：通信板卡损坏R22与主板损坏R23相比，标度值为4 ；电源损坏R21与主板损坏R23相比，标度值为6 ；电源损坏R21与通信板卡损坏R22相比，标度值为2。 [0065] (2) determines how often the weight coefficient of the second layer causes: how often the weight coefficient matrix of the reasons for establishing unit according to a second order Ni layer (the second sequence of the present embodiment uses the failure analysis unit in the second embodiment the order layer), and to establish how often the weight coefficient matrix f2 3X3 for the second layer causes; values ​​how often the weight coefficient matrix f2 element f2 (X, y) is the X-th compared with that of y reason the resulting scale value, wherein, f2 (x, y) represents how often the line X weighting coefficient matrix column element f2 of y; values ​​x, y are 1, 2 and 3; how often the weight coefficient matrix is ​​established query from the knowledge base unit to the following result: a communication board damage compared to damage to the motherboard R22 R23, the scale is 4; R21 damage to the power board damage compared to R23, the scale value of 6; and R21 power communication board damage card is damaged compared to R22, the scale value is 2.

[0070] 频繁程度权重系数矩阵建立単元将频繁程度权重系数矩阵f2的所有元素的数值均发送至频繁程度权重系数计算单元，频繁程度权重系数计算单元计算频繁程度权重系数矩阵f2的最大特征值所对应的特征向量，并将得到的特征向量归ー化，归ー化得到的特征向量为[70. 1%，19. 3%，10. 6%]，归ー化后向量中的各元素值按第二顺序对应第二层各原因的严重程度权重系数，即电源损坏R21、通信板卡损坏R22和主板损坏R23的严重程度权重系数分别为70. 1%、19. 3% 和10. 6% ； [0070] how often the weight coefficient matrix established radiolabeling element the value of all the elements on how frequently weight coefficient matrix f2 are sent to the weighting coefficient how often the weight calculation unit how often the weight coefficient calculation unit calculates how often the weight coefficient matrix f2 is the maximum eigenvalue corresponding eigenvectors, and the resulting normalized eigenvectors ー, feature vector normalization is obtained ー of [70.1%, 19.3%, 10.6%], the value of each element in the vector of normalized ーa second order, corresponding to each of the second layer causes the severity weighting coefficient, i.e. the power damage R21, R22 and communications boards damage R23 board damage severity weighting factor is 70.1%, 19.3% and 10.6, respectively, %;

[0071] 步骤19，故障树建立单元从故障分析单元读取所述故障现象，从严重程度权重系数计算单元读取各原因的严重程度权重系数，从频繁程度权重系数计算单元读取各原因的频繁程度权重系数，并建立故障树，其中，如图3所示，故障树的树根为故障现象，即“电脑屏幕无显示”，故障现象及各原因，即“电脑屏幕无显示”，主机损坏Rn、屏幕损坏R12和接线损坏R13,以及电源损坏R21、通信板卡损坏R22和主板损坏R23，构成故障树的各组分，各组分按分解关系排列，同一组分分解出的各原因按照严重程度权重系数从大到小进行排列，即由故障现象分解出的直接原因按主机损坏Rn、屏幕损坏R12和接线损坏R13顺序排列，而由主机损坏R11分解出的第二层原因按主板损坏R23、通信板卡损坏R22和电源损坏R21排列；并表示各组分和由其分解出的下ー层原因间的逻辑关系 [0071] Step 19, the fault tree creation unit fault analysis unit reads from the symptoms, the severity of the weight coefficient calculated from the weight unit reads the severity of the weight of each weighting coefficients reason, calculated from the weight coefficient of each unit to read how often cause weight how often the weighting coefficient, and to establish the fault tree, which, shown in Figure 3, the fault tree roots fault phenomenon, that is, "the computer screen no display" failure phenomenon and various reasons, that is, "the computer screen no display" host each of the causes of damage Rn, damage to the screen and damage to the wiring R12 R13, and a power supply damage R21, R22 and communications boards damage damage to the motherboard R23, the components constituting the fault tree, the components are arranged in exploded relationship, the decomposition of the same component severe weight coefficient according to the degree of weight are arranged in descending, i.e. the direct cause of the decomposition by the failure phenomenon damaged by host Rn, damage to the screen and damage to the wiring R12 R13 order, and the second layer by the decomposition of R11 reasons damage by the host motherboard damage R23, R22 and communications boards damaged power arranged damage R21; and represents the logical relationship between the various components and by reason of the lower layer is decomposed ー及为各原因标注自身的频繁程度权重系数，所述逻辑关系由故障树建立单元从所述知识库中获取，在本实施例中，第一层与故障现象之间的逻辑关系为“或”，第二层各原因与主机损坏R11之间的逻辑关系也为“或”。 And how often denoted by their weight coefficients for the reason, the logical relation established by the fault tree acquiring means from said knowledge base, in the present embodiment, the logical relationship between the first layer and the failure type of "or" the second layer of each host Cause damage logical relationship between R11 is also "or."

[0072] 以上所述仅为本发明较佳的实施方式，并非用来限定本发明的实施范围，但凡在本发明的保护范围内所做的等效变化及修饰，皆应认为落入了本发明的保护范围内。 [0072] The foregoing is only preferred embodiments of the present invention, not intended to limit the scope of embodiments of the present invention, provided that equivalent variations and modifications made within the scope of the present invention, are to be considered to fall within the present within the scope of the invention.

Claims (2)

Translated from Chinese

1. 一种故障树的建立方法，其特征在于，包括如下步骤： 步骤1，故障分析单元根据输入的故障现象从知识库中获得引起所述故障现象的各直接原因，并将各直接原因设定为第一层；故障分析单元通过Ru代表与所述故障现象有关的各原因，i代表原因所在的层数，j代表原因Ru在第i层的序号，对应第i层的j的取值为I至Ni的所有自然数，其中，Ni为第i层的原因的数量，i=l的各原因为所述直接原因；步骤2 :故障分析单元计算第一层的直接原因的数量N1 ； 步骤3，故障分析单元执行j=l，i=l，之后执行步骤4 ； 步骤4，故障分析单元通过查询知识库判断原因Ru是否存在可分解的下一层原因，如存在则执行步骤5，如不存在则执行步骤6 ； 步骤5，故障分析单元从知识库中读出由原因Ru分解出的原因，并将分解出的原因列至第i+Ι层，之后执行步骤6; 步骤6，故障分析单元 1. A method for establishing a fault tree, characterized by comprising the following steps: Step 1, to obtain the respective unit fault analysis of the direct causes of the phenomenon of failure to prevent the phenomenon from the knowledge base input, and each provided direct cause as a first layer; each cause of the failure analysis unit by Ru represents the phenomenon of the failure, the reason i represents the number of layers, the number j represents reason Ru layer i, j corresponding to the value of the i-th layer I to all natural numbers Ni, where, Ni is the number of i-th layer reason, each of the i = l reasons for the direct cause; step 2: N1 number of the direct cause of the failure analysis module calculates a first layer; step 3, the fault analysis unit performs j = l, i = l, after performing step 4; step 4, whether there is a fault analysis unit Ru decomposable reasons next layer is determined by querying the knowledge base reasons, such as is present step 5 is performed, as does not exist, step 6; step 5, the fault reason analysis unit reads out the decomposition by the reason Ru from the knowledge base, and the reason the decomposition of th to i + Ι layer, after performing step 6; step 6, fault analysis unit执行j=j+l，之后执行步骤7 ； 步骤7，故障分析单元判断j是否小于等于Ni,如是则执行步骤4，如否则执行步骤8 ；步骤8，故障分析单元根据查询结果判断第i层各原因是否均无法分解，如是则执行步骤11，如否则执行步骤9; 步骤9，故障分析单元计算第i层分解出的第i+Ι层的原因的数量Ni+1，之后执行步骤10 ； 步骤10，故障分析单元执行i=i+l，j=l，之后执行步骤4 ; 步骤11，严重程度权重系数矩阵建立单元从故障分析单元读取各层原因，计算最大层数m，并执行i=l，之后执行步骤12 ； 步骤12，确定第i层原因的严重程度权重系数，之后执行步骤13 ;确定严重程度权重系数的方法如下： 严重程度权重系数矩阵建立单元对第i层原因按第i顺序排列，并针对第i层原因建立Ni X Ni的严重程度权重系数矩阵Ui ;严重程度权重系数矩阵Ui的元素Ui (X，y)的数值为第X个原因与第y个原 Performing j = j + l, after performing step 7; step 7, the fault analysis unit determines whether j is less Ni, case step 4 is performed, as otherwise step 8; step 8, the failure analysis unit based on the query results to determine the i-th layer whether each reason are not decomposed, in the case the step 11, as otherwise step 9; step 9, the failure analysis module calculates the number of the reasons of i + Ι layer i-th layer decomposed Ni + 1, after execution of the step 10; step 10, the fault analysis unit performs i = i + l, j = l, after performing step 4; step 11, the severity of the weight coefficient matrix layers reasons establishing unit reads from the failure analysis unit calculates the maximum number of layers m, and perform i = l, after performing step 12; step 12, determine the severity of the weight coefficient of the i-layer reason, after performing step 13; the method of determining the severity of the weighting factor as follows: severity weighting coefficient matrix creating unit to the first i-layer reasons press the i-th order, and to establish the severity of the weight coefficient matrix Ui Ni X Ni for the i-th layer causes; numerical severity weighting coefficient matrix Ui elements Ui (X, y) for the first X reason and the y-th of the original因相比得到的标度值，其中，ui (x，y)表示严重程度权重系数矩阵ui的第X行第y列元素；x、y的取值均为从I至Ni的所有自然数；严重程度权重系数矩阵建立单元将严重程度权重系数矩阵ui的所有元素的数值均发送至严重程度权重系数计算单元，严重程度权重系数计算单元计算严重程度权重系数矩阵ui的最大特征值所对应的特征向量，并将得到的特征向量归一化，归一化后向量中的各元素值按第i顺序对应第i层各原因的严重程度权重系数； 严重程度权重系数矩阵建立单元确定严重程度权重系数矩阵ui的各元素的数值的方法为：使第i层的每个原因均与第i层的所有原因进行两两比较，第X个原因与第y个原因同样严重则标度值为1，第X个原因比第y个原因稍微严重则标度值为3，第X个原因比第y个原因明显严重则标度值为5，第X个原因比第y个原因强烈严重则标度值 Scale value obtained by the comparison, where, ui (X, y) indicates the severity of the weight coefficient matrix row X y-th column element ui; X, y values ​​are from I to all of the natural numbers Ni; severe the degree of weight coefficient matrix creating unit to the severity of the weight coefficient matrix values ​​of all elements of ui are transmitted to severe weight coefficient degree of weight calculating unit, the severity of the weighting coefficient calculating unit calculates the severity of the weight coefficient matrix largest eigenvalue value of ui corresponding to the and the resulting feature vector normalization, the normalization of each element values ​​in the vector according to the i-th order corresponding i-th layer severity of the weighting coefficients of reasons; the severity of the weight coefficient matrix creating unit determines the severity of the weight coefficient matrix numerical methods for each element ui: Causes each i-th layer and pairwise comparisons were performed for all-cause i-th layer, the first and the second y X reason reason is as serious as the scale value of 1, X reason is slightly worse than the first y reason the scale value is 3, the X reason than the obvious reason of serious y scale value is 5, X reason strong reason serious than the y-scale value7，第X个原因比第y个原因极端严重则标度值为9 ;x、y取值互置的元素ui (x，y)的数值互为倒数，X、y取值相同的元素ui (X，y)的数值为I ;所述严重程度权重系数矩阵建立单元从知识库获得对第i层的所有原因进行针对严重程度进行两两比较的标度值； 步骤13，严重程度权重系数矩阵建立单元执行i=i+l，之后执行步骤14 ； 步骤14，严重程度权重系数矩阵建立单元判断i是否小于等于m，如是则执行步骤12，如否则执行步骤15 ； 步骤15，频繁程度权重系数矩阵建立单元从故障分析单元读取各层原因，计算最大层数m，并执行i=l，之后执行步骤16 ； 步骤16，确定第i层原因的频繁程度权重系数，之后执行步骤17 ;确定频繁程度权重系数的方法如下： 频繁程度权重系数矩阵建立单元对第i层原因按第i顺序排列，并针对第i层原因建立NiXNi的频繁程度权重系数矩阵fi ;频繁程 7, the X reason extremely serious than the first y reason the scale is 9; values ​​x, y values ​​mutually opposite elements ui (x, y) of the reciprocal, X, y values ​​of the same elements ui (X, y) has a value of i; the severity of the weight coefficient matrix creation unit obtained from the knowledge base for all the reasons i-th layer is pairwise comparison for severity scale value; step 13, the severity of the weight coefficient matrix establishing unit executes i = i + l, after performing step 14; step 14, the severity of the weight coefficient matrix establishing unit determines whether i is less than equal to m, the case of the step 12, as otherwise, executing step 15; step 15, how frequently weight establishing unit coefficient matrix read from the failure analysis unit layers reasons, calculating the maximum number of layers m, and executes i = l, after performing step 16; step 16, it is determined how often the weight of the i layer weight coefficient reason, after performing step 17; the method of determining how often the weight coefficients are as follows: how often establishing unit weight coefficient matrix of the i-th layer are arranged in the i-th order reasons, and to establish how often fi NiXNi weight coefficient matrix for the i-th layer causes; how frequently权重系数矩阵fi的元素fi (X，y)的数值为第X个原因与第y个原因相比得到的标度值，其中，fi(x，y)表示频繁程度权重系数矩阵fi的第X行第I列元素；χ、I的取值均为从I至Ni的所有自然数；频繁程度权重系数矩阵建立单元将频繁程度权重系数矩阵fi的所有元素的数值均发送至频繁程度权重系数计算单元，频繁程度权重系数计算单元计算频繁程度权重系数矩阵fi的最大特征值所对应的特征向量，并将得到的特征向量归一化，归一化后向量中的各元素值按第i顺序对应第i层各原因的频繁程度权重系数； 频繁程度权重系数矩阵建立单元确定频繁程度权重系数矩阵fi的各元素的数值的方法为：使第i层的每个原因均与第i层的所有原因进行两两比较，第X个原因与第y个原因同样频繁则标度值为I，第X个原因比第y个原因稍微频繁则标度值为2，第X个原因比第y个原因明显 Numerical weighting coefficient matrix fi elements fi (X, y) is a scaling value in comparison of X reason and y-reason, where, fi (X, y) indicates how often the weight coefficient matrix fi of X row column I elements; χ, I values ​​are from I to all natural numbers Ni; and how often the weight coefficient matrix creating unit frequently degree weight coefficient matrix of all elements fi of values ​​are transmitted to the weighting coefficient how often the weight calculation unit , how often the weight coefficient calculation unit calculates how often the weight coefficient matrix largest eigenvalue value fi corresponding to the, and the resulting feature vector normalization, the normalization of each element values ​​in the vector according to the i-th order first correspondence how often the weighting coefficients of the reasons i-layer; coefficients of unit determines how often the weight coefficient matrix the value of each element of fi matrix established as how often the right: each cause of the first i-layer are carried out with all the reasons i-th layer pairwise comparison, the first reason and the second X y reason the same frequency scale is I, X reason of slightly more frequently than the first y reason the scale value is 2, the X-th than the reason for the apparent reason y繁则标度值为4，第X个原因比第y个原因强烈频繁则标度值为6，第X个原因比第y个原因极端频繁则标度值为8 ;x、y取值互置的两个元素fi (X，y)的数值互为倒数，x、y取值相同的元素fi(x，y)的数值为I ;所述频繁程度权重系数矩阵建立单元从知识库获得对第i层的所有原因进行针对频繁程度进行两两比较的标度值； 步骤17，频繁程度权重系数矩阵建立单元执行i=i+l，之后执行步骤18 ； 步骤18，频繁程度权重系数矩阵建立单元判断i是否小于等于m，如是则执行步骤16，如否则执行步骤19 ； 步骤19，故障树建立单元从故障分析单元读取所述故障现象，从严重程度权重系数计算单元读取各原因的严重程度权重系数，从频繁程度权重系数计算单元读取各原因的频繁程度权重系数，并建立故障树，故障现象和各原因构成故障树的各组分，故障树的树根为故障现象，各 Traditional value of the scale 4, X reason strong reason frequently than the y value of the scale 6, the first X terminal reason frequent reason than the y value of the scale 8; x, y values ​​of the cross values ​​of the two opposing elements fi (X, y) is reciprocal, x, y values ​​of the same element value fi (x, y) is I; how often the weight coefficient matrix for establishing unit obtained from the knowledge base All Cause i-th layer is performed scale values ​​pairwise comparison for the frequency of; the step 17, how often the weight coefficient matrix creating unit performs i = i + l, after performing step 18; step 18, how often the weight coefficient matrix established unit determines whether or not i is equal to less than m, the case of the step 16, as otherwise step 19; step 19, the fault tree creation unit fault analysis unit reads the failure phenomenon, from the weight coefficient calculation unit reads the severity of each right reasons the severity of the weighting coefficient, calculated from the weight coefficient how often the right unit reads how often the weighting coefficients of the cause, and to establish fault tree, fault, and each of the causes for the fault tree of the components, roots fault tree of symptoms, each分按分解关系排列，由同一组分分解出的各原因按照严重程度权重系数从小到大或从大到小进行排列，并表示出各组分和由其分解出的下一层原因间的逻辑关系，及为各原因标注自身的频繁程度权重系数，所述逻辑关系由故障树建立单元从所述知识库中获取。 Press arrangement relationship decomposition points, each by the same reason the decomposition of the components in accordance with the severity of the weighting factor for ascending or descending order, and shows the logical and between the various components exploded therefrom reason the next layer out relationship, and how often the own label weighting coefficient for the reason, the logical relationship is established by the fault tree acquiring means from said knowledge base.

2.根据权利要求I所述的建立方法，其特征在于：所述建立方法为针对电子信息系统的故障检测的建立方法。 The establishment of the method of claim I, wherein: the establishing method for establishing a fault detection method for electronic information system.